Waste collection is an important municipal service that charges large expenditures to waste management (WM) system. In this study, a hierarchical structure is proposed in order to minimize total cost of waste collection routing problem. Moreover, in second stage destructive environmental effects of waste transportation are minimized concurrently through taking advantage of a road/rail transportation system. In the proposed multimodal transportation system, waste packs are transferred to final destination while travel time and risk of environmental threatening is minimized. The discussed problem is formulated mathematically in two stages. In the first stage, a household waste collection routing problem is formulated while, in second stage a multimodal transportation system is routed to transfer waste packs to final destination through roads and railroads. In order to solve the proposed NP hard models, an improved genetic algorithm is developed. Comparison of the obtained results with those of GAMS for small-size samples validates the proposed models.

In the global critical economic scenario, inflation plays a vital role in deciding optimal pricing of goods in any business entity. This article presents two single-vendor single-buyer integrated supply chain inventory models with inflation and time value of money. Shortage is allowed during the lead time and it is partially backlogged. Lead time is controllable and can be reduced using crashing cost. In the first model, we consider the demand of lead time follows a normal distribution, and in the second model, it is considered distribution-free. For both cases, our objective is to minimize the integrated system cost by simultaneously optimizing the order quantity, safety factor, lead time and number of lots. The discounted cash flow and classical optimization technique are used to derive the optimal solution for both cases. Numerical examples including the sensitivity analysis of system parameters is provided to validate the results of the supply chain models.

In the recent years, issues like high competitive pressure, globalization, business difficulties, resources limits, technological complications and activities specialization, fast changes in environment, etc. have caused organizations to reconsider their management methods. As a result, they are looking forward to branding new strategies in order to achieve competitive advantages. Focusing on main competences and outsourcing most of the activities are some of these strategies. Assessment management and selecting the appropriate contractor who holds adequate efficiency is of critical importance for having a project accomplished in time and with foreseen resources. Various qualitative and quantitative factors of different importance are involved in contractors’ assessment and should be taken into account before decision making. In this paper, once the factors are identified using fuzzy screening method, they are prioritized according to their importance by means of fuzzy hierarchical analysis.

Enterprise architecture, with detailed descriptions of the functions of information technology in the organization, tries to reduce the complexity of technology applications resulting in tools with greater efficiency in achieving the objectives of the organization. Enterprise architecture consists of a set of models describing this technology in different components performance as well as various aspects of the applications in any organization. Therefore, information technology development and maintenance management can perform well within organizations. This study aims to suggest a method to identify different types of services in service-oriented architecture analysis step that applies some previous approaches in an integrated form and, based on the principles of software engineering, to provide a simpler and more transparent approach through the expression of analysis details. Advantages and disadvantages of proposals should be evaluated before the implementation and costs allocation. Evaluation methods can better identify strengths and weaknesses of the current situation apart from selecting appropriate model out of several suggestions, and clarify this technology development solution for organizations in the future. We will be able to simulate data and processes flow within the organization by converting the output of the model to colored Petri nets and evaluate and test it by examining various inputs to enterprise architecture before implemented in terms of reliability and response time. A model of application has been studied for the proposed model and the results can describe and design architecture for data.

In many quality control applications, the quality of a process or product is explained by the relationship between response variable and one or more explanatory variables, called a profile. In this paper, a new fuzzy EWMA control chart for phase II fuzzy profile monitoring is proposed. To this end, we extend EWMA control charts to its equivalent Fuzzy type and then implement fuzzy ranking methods to determine whether the process fuzzy profile is under or out of control. The proposed method is capable of identifying small changes in process under condition of process profile explaining parameters vagueness, roughness and uncertainty. Determining the source of changes, this method provides us with the possibility of recognizing the causes of process transition from stable mode, removing these causes and restoring the process stable mode.

The present work deals with the comparison of four multi response optimization methods, viz. multiple response signal-to-noise (MRSN) ratio, weighted signal-to-noise (WSN) ratio, Grey relational analysis (GRA), and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian) methods taking a case study in turning mild steel specimen using HSS cutting tool. The various factors like cutting speed, feed rate, depth of cut and coolant flow rate are considered as the input process variables, while the material removal rate (MRR), surface roughness (SR) and specific energy consumption (SEC) are considered as various performance characteristics. One set of experimental data is analyzed using the standardized procedures. The optimization performances of these four methods are compared. The results show that MRSN ratio method proves to be the best optimization method. It is found that the feed rate has a highest impact on the overall performance as compared to other process parameters.

Fault detection process (FDP) and Fault correction process (FCP) are important phases of software development life cycle (SDLC). It is essential for software to undergo a testing phase, during which faults are detected and corrected. The main goal of this article is to allocate the testing resources in an optimal manner to minimize the cost during testing phase using FDP and FCP under dynamic environment. In this paper, we first assume there is a time lag between fault detection and fault correction. Thus, removal of a fault is performed after a fault is detected. In addition, detection process and correction process are taken to be independent simultaneous activities with different budgetary constraints. A structured optimal policy based on optimal control theory is proposed for software managers to optimize the allocation of the limited resources with the reliability criteria. Furthermore, release policy for the proposed model is also discussed. Numerical example is given in support of the theoretical results.

In this paper, group scheduling problem in no-wait flexible flowshop is considered by considering two stages with group sequence-dependent setup times and random breakdown of the machines. Genetic algorithm and simulated annealing based heuristics have been proposed to solve the problem. The primary objective of scheduling is to minimize the maximum completion time of the jobs for two classes of small and large scale problems. Computational results show that both GA and SA algorithms perform properly, but SA appeared to provide better results for both small and large scale problems.

Component-based software system (CBSS) development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.

In this paper, a method for severity fault diagnosis of ball bearings is presented. The method is based on wavelet packet transform (WPT), statistical parameters, principal component analysis (PCA) and support vector machine (SVM). The key to bearing faults diagnosis is features extraction. Hence, the proposed technique consists of preprocessing the bearing fault vibration signal using statistical parameters and energy obtained through the application of Db8- WPT at the third level of decomposition. After feature extraction from vibration signal, PCA is employed for dimensionality reduction. Finally, particle swarm optimization with passive congregation-based support vector machine is used to classify seven kinds of bearing faults. The classification results indicate the effectiveness of the proposed method for severity faults diagnosis in ball bearings.